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Prediction and Assessment of Ammonium Bisulfide Corrosion Under Refinery Service Conditions - Part 3

Picture for Prediction and Assessment of Ammonium Bisulfide Corrosion Under Refinery Service Conditions - Part 3
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Summarizes results from Phase III of the joint industry program (JIP) on refinery alkaline sour water (ammonium bisulfide) corrosion. Phase III included a comprehensive engineering analysis of data from all three phases of the Sour Water JIP.

Product Number: 51317--8929-SG
ISBN: 8929 2017 CP
Author: Richard Horvath
Publication Date: 2017
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$20.00
$20.00

This paper summarizes results from Phase III of the joint industry program (JIP) on refinery alkaline sour water (ammonium bisulfide) corrosion. Phase III included a comprehensive engineering analysis of data from all three phases of the Sour Water JIP and the development of “H2S tie-in plots” based on a single parameter (H2S partial pressure), replacing the isocorrosion diagrams based on NH3 partial pressure developed in Phase II, and linking with the H2S isocorrosion diagrams based on H2S partial pressure developed in Phase I. These H2S tie-in plots enabled corrosion rate data for carbon steel and five commonly used corrosion resistant alloys to be contiguously modeled across the entire range of conditions tested ― six orders of magnitude of H2S partial pressure, from approximately 0.00004 to 150 psia (0.0003 to 1,000 kPa absolute) ― to fully characterize effects of H2S-dominated, NH3-dominated and intermediate sour water conditions. The results clearly demonstrated that NH4HS concentration, flow velocity (wall shear stress), H2S partial pressure, and free cyanide concentration in the NH4HS solution are the key parameters driving severity of refinery sour water corrosion. The effect of temperature was also clarified. Substantial differences in corrosion behavior of carbon steel from the corrosion resistant alloys were observed in low NH4HS concentrations at intermediate H2S partial pressures, where corrosion rates of carbon steel and all the alloys exhibited surprisingly significant dips and peaks on the H2S tie-in plots. The results and analyses of data were synthesized into an enhanced software tool to predict corrosion rates for the six materials (carbon steel, stainless steels, and nickelbased alloys) evaluated in the program, addressing a broad range of environmental conditions encompassed by all three phases of the Sour Water JIP.

 

Key words: sour water, ammonium bisulfide, NH4HS, hydrogen sulfide, H2S, ammonia, NH3, partial pressure, tie-in plots, temperature, cyanide, velocity, wall shear stress, materials selection, corrosion prediction model, software

This paper summarizes results from Phase III of the joint industry program (JIP) on refinery alkaline sour water (ammonium bisulfide) corrosion. Phase III included a comprehensive engineering analysis of data from all three phases of the Sour Water JIP and the development of “H2S tie-in plots” based on a single parameter (H2S partial pressure), replacing the isocorrosion diagrams based on NH3 partial pressure developed in Phase II, and linking with the H2S isocorrosion diagrams based on H2S partial pressure developed in Phase I. These H2S tie-in plots enabled corrosion rate data for carbon steel and five commonly used corrosion resistant alloys to be contiguously modeled across the entire range of conditions tested ― six orders of magnitude of H2S partial pressure, from approximately 0.00004 to 150 psia (0.0003 to 1,000 kPa absolute) ― to fully characterize effects of H2S-dominated, NH3-dominated and intermediate sour water conditions. The results clearly demonstrated that NH4HS concentration, flow velocity (wall shear stress), H2S partial pressure, and free cyanide concentration in the NH4HS solution are the key parameters driving severity of refinery sour water corrosion. The effect of temperature was also clarified. Substantial differences in corrosion behavior of carbon steel from the corrosion resistant alloys were observed in low NH4HS concentrations at intermediate H2S partial pressures, where corrosion rates of carbon steel and all the alloys exhibited surprisingly significant dips and peaks on the H2S tie-in plots. The results and analyses of data were synthesized into an enhanced software tool to predict corrosion rates for the six materials (carbon steel, stainless steels, and nickelbased alloys) evaluated in the program, addressing a broad range of environmental conditions encompassed by all three phases of the Sour Water JIP.

 

Key words: sour water, ammonium bisulfide, NH4HS, hydrogen sulfide, H2S, ammonia, NH3, partial pressure, tie-in plots, temperature, cyanide, velocity, wall shear stress, materials selection, corrosion prediction model, software

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Picture for 10349 Prediction and Assessment of Ammonium Bisulfide Corrosion Under Refinery Sour Water
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10349 Prediction and Assessment of Ammonium Bisulfide Corrosion Under Refinery Sour Water Service Conditions-Part 2

Product Number: 51300-10349-SG
ISBN: 10349 2010 CP
Author: Richard J. Horvath, Vishal V. Lagad, Sridhar Srinivasan and Russell D. Kane
Publication Date: 2010
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This Phase II work in NH3-dominated sour waters studied the impact of several process variables including NH4HS concentration, NH3 partial pressure, H2S partial pressure, temperature, cyanide concentration, and velocity (wall shear stress).
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06576 PREDICTION AND ASSESSMENT OF AMMONIUM BISULFIDE CORROSION UNDER REFINERY SOUR WATER SERVICE CONDITIONS

Product Number: 51300-06576-SG
ISBN: 06576 2006 CP
Author: Richard J. Horvath, Michael S. Cayard, Russell D. Kane
Publication Date: 2006
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This paper summarizes results of a joint industry program (JIP) to address ammonium bisulfide (NH 4 HS) corrosion in H 2 S-dominated alkaline sour waters typically found in refinery services such as the reactor effluent air cooler (REAC) systems of hydroprocessing units.
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06577 PREDICTION OF AMMONIUM BISULFIDE CORROSION AND VALIDATION WITH REFINERY PLANT EXPERIENCE

Product Number: 51300-06577-SG
ISBN: 06577 2006 CP
Author: Richard J. Horvath, Russell D. Kane, Vishal V. Lagad, Michael S. Cayard, Walter G. Giesbrecht
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